Investigating How Age, Number of Bedrooms, and Square Footage Determine House Prices Course Project Part C Math533 – Applied Managerial Statistics Contents 1. Overview of the Problem and Questions...…………………...................................3 2. List of Variables…………………………………………………………..…………......3 3. Sources of Data……………………………………………………………………........4 4. Data……………………………………………………………………………………….5 5.
All of these contribute to the biggest financial weakness of the Utah Symphony, which is its profitability. The symphony’s bottom line profit for 2000-2001 was only $116,308, which is less that 1% of its total revenues and the forecast for 2001-2002 paints an even bleaker picture with bottom line profit projected to be only $2,042. A leadership strength of Keith Lockhart is his in-depth
The best price to consume the maximum consumer surplus and get the highest revenue is to charge a total of $8,000 for a both dorm room and meal plan. Chapter 9 2. Problem #5, p. 221 in text. Total cost = 200 + 50 q Market demand: P = 290 –(1/3) Q Number of firms in market: n=14 The output level that maximizes profit: q = (a – c) / [(n+1)*b] q
The primary customers of KR+H cabinetry are those who want to optimize the amount of useable space in their homes that stock cabinets cannot provide. The industry in 1992 was comprised of 61% stock cabinetry, and custom cabinets similar to those produced by KR+H comprised of only 20%. This is down from 26% in 1989 resultant from poor economic conditions between 1989 and 1992. KR+H uses a direct sale to consumer approach that only accounted for 2% of total industry sales. Industry sales by use of cabinet dealers and distributors contributed for 31% and 30% respectively.
Measures of Central Tendency & Frequency Distribution Tables QNT 321/ Introduction to Business Statistics Appendix J of Statistical Techniques in Business and Economics consisted of a Real Estate dataset, which included: selling prices, number of bedrooms, size of the homes in square feet, pool, distance from the center of the city, township, garage attached, and number of bathrooms. In addition to calculating the measures of tendency for selling price (x1), number of bedrooms (x2), size of home in square feet (x3), distance from the center of the city in miles (x5), and number of bathrooms (x8), the data was analyzed to create 5 and 7 class frequency distribution tables for each. From what was gathered, the mean selling price
The housekeeping module prompts for and accepts a wholesale price. The detail module prompts for and accepts the retail price, computes the profit, and displays the result. The end-of-job module displays the message “Thanks for using this program”. DetailLoop() DetailLoop() Main Main EndofJob() EndofJob() HouseKeeping() HouseKeeping() Main Start CALL HouseKeeping CALL DetailLoop CALL EndofJob Stop HouseKeeping() Start STRING WORD = house STRING Word = “Enter Random Word:” OUTPUT Word INPUT randomWord Return DetailLoop() Start String Left = Flipforward String Right = Flipbackward randomWord = Word If randomWord is > Word then Left Else If randowmWord is < Word the Right endif Return EndofJob() Start OUTPUT Define Word Return INPUT NAME | DESCRIPTION | DATA TYPE/LENGHT | randomWord | Target word ‘house’ | String | | | | | | | | | | WORK AREA NAME | DESCRIPTION | DATA TYPE/LENGHT | | | | OUTPUT NAME | DESCRIPTION | DATA TYPE/LENGHT | Word | Enter random word | String | Flipforward | Word not on page, flip forward | String | Flipback | Word not on page, flip backward” | String | Define Word | Read definition | String | Left | Flip 1 page backward | Number | Right | Flip 1 page forward | Number |
Tom’s Used Mustangs Report Robert Davy GM533 Applied Managerial Statistics GM533 – Course Project February 16, 2011 Executive Summary I was hired to review the information collected by Tom of Tom’s Used Mustangs to determine what features if any affect the sales price of used Mustangs. The results of the tests will be used to more accurately create a competitive sales price for the cars on Tom’s lot, as well as provide assistance in developing a sales price for all future purchases and sales. After performing several statistical tests I have determined that there is evidence certain features do indeed affect the sales price. However, knowing that certain features have an effect on the sales price of the used Mustang, does not necessarily assist in determining what that sales price should be. The sections below will detail the
Jiggz Final Project 12 December 2011 Business 508 – Decision Science for Business Professor: Paul Fioramonti, M.S., Applied Mathematics REGRESSION MODEL TO PREDICT LOCAL HOUSING FAIR MARKET VALUE (OAK HARBOR, WA 98277) Purpose: | I decided to choose this subject to determine what kind of methodology is used by theCounty Treasurer in determining the fair market value of housing in the area for property tax purposes. Based from the last Property Tax Statement from the Country Treasurer, the house was assessed at a value of $339,596.00 for the current year 2011. Having gained knowledge of Regression Analysis, I would like to use this methodology to determine local housing fair market value using multiple regression analysis. | Overview: |
500 @ $4.58 = $2,290 200 @ 4.60 = 920 700 $3,210 Ending inventory at FIFO cost. (2) 100 @ $4.10 = $ 410 600 @ 4.20 = 2,520 700 $2,930 Ending inventory at LIFO cost. (3) $9,240 cost of goods available for sale ÷ 2,100 units available for sale = $4.40 weighted-average unit cost. 700 units X $4.40 = $3,080 Ending inventory at weighted-average cost. (b) (1) LIFO will yield the lowest gross profit because this method will yield the highest cost of goods sold figure in the situation presented.
If this monopolistically competitive firm maximizes profit, it will 26. Suppose the minimum possible price of constructing homes is $50 per square foot. As a result of a sharp drop in the demand for home construction, the equilibrium price of home construction falls to $40 per square foot. Assuming the home construction industry is perfectly competitive and there are no specialized inputs, firms